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We're interested in the intersection of data science, systems architecture, data modeling and devops.

Our goal is vendor neutral, language agnostic, platform independent, linearly scaling, latency aware, automated solutions centered around the acquisition, cleansing, governing, processing and analyzing of data. Big data or small data, getting it wrong means extra work, missed opportunities and crashed spaceships.

As a software engineer you are faced with both an ever-increasing amount of data, and ever-increasing choices on how to access and manage it. As a data professional you are either inspired or overwhelmed by the myriad technologies appearing on the scene. And all of us experience pain when data pipelines are treated like an art instead of a science. Art is beautiful and takes a lot of skill, but it can't be reproduced and no one else knows how you arrived at the result.

Please note that this is a technical engineering group focused on data-oriented architectures and use-cases. All levels and experiences are welcome to attend and present. The best way to learn is to teach!

Since I'm currently on the board of the DAMA Portland Metro Chapter (Data Administration and Management Association) we are cross-posting our chapter meetings here, but please feel free to schedule your own meetings and suggest other topics in the discussions-- or directly to the meetup organizers. We'd love to hear from you!

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